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Researcher · Hebei University · China

Xiaobing Yan

Xiaobing Yan publishes mostly in Electrical and Electronic Engineering, Materials Chemistry and Geophysics, on topics such as Advanced Memory and Neural Computing, Ferroelectric and Negative Capacitance Devices and Semiconductor materials and devices.

ORCID 0000-0002-6335-336X OpenAlex
World rank
#804,938
of 7,710,434 ranked researchers
Rank in China
#108,896
of 978,568
Works
38
Citations
1.1k
Citations per work
29.5
h-index
15
i10-index 18Top 30% in Electrical and Electronic Engineering
Xiaobing Yan

What does Xiaobing Yan research?

Xiaobing Yan's work is mostly in Engineering (53%), Materials Science (9%), Earth and Planetary Sciences (6%).

Physical Sciences: 28 works · 73.3% of their workEngineering: 20 works · 52.7% of their workElectrical and Electronic Engineering: 19 works · 50.0% of their workBiomedical Engineering: 1 works · 2.7% of their workMaterials Science: 3 works · 8.9% of their workMaterials Chemistry: 3 works · 8.9% of their workEarth and Planetary Sciences: 2 works · 6.3% of their workGeophysics: 2 works · 6.3% of their workComputer Science: 2 works · 5.4% of their workArtificial Intelligence: 2 works · 5.4% of their workEverything else: 9 works · 23.1% of their workLife Sciences: 1 works · 3.6% of their workNeuroscience: 1 works · 3.6% of their workCognitive Neuroscience: 1 works · 3.6% of their workTHEIR WORKXiaobing Yan38works
Life Sciences4%Physical Sciences73%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Engineering2052.7%
    2. Materials Science38.9%
    3. Earth and Planetary Sciences26.3%
    4. Computer Science25.4%
  2. Everything else923.1%
    1. Neuroscience13.6%
  1. 1Electrical and Electronic Engineering50% of their works
  2. 2Materials Chemistry9% of their works
  3. 3Geophysics6% of their works
  4. 4Artificial Intelligence5% of their works
  5. 5Cognitive Neuroscience4% of their works
  6. 6Biomedical Engineering3% of their works

Research topics

Which keywords describe Xiaobing Yan's research?

The keywords of their largest research topics: Neuromorphic Computing, Memristor, Resistive Switching, Ferroelectricity, Hafnium Oxide, Atomic Layer Deposition, High-k Dielectrics and Machine Learning.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 18 words, with their numbers
  1. Neuromorphic Computing382 topics
  2. Memristor211 topic
  3. Resistive Switching211 topic
  4. Ferroelectricity171 topic
  5. Hafnium Oxide171 topic
  6. Atomic Layer Deposition61 topic
  7. High-k Dielectrics61 topic
  8. Machine Learning62 topics
  9. Cortical Networks41 topic
  10. Earthquakes41 topic
  11. Neuronal Oscillations41 topic
  12. Subduction41 topic
  13. Earthquake Detection31 topic
  14. Electrode Arrays31 topic
  15. Neural Stimulation31 topic
  16. Neuromorphic Photonics31 topic
  17. Photonic Reservoir Computing31 topic
  18. Seismic Signals31 topic

Where does Xiaobing Yan work?

Xiaobing Yan's main affiliation in the publication record is Hebei University, China.

How many publications and citations does Xiaobing Yan have?

OpenAlex counts 38 works and 1,120 citations for Xiaobing Yan, an h-index of 15, ranking #804,938 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Other researchers named Xiaobing Yan

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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